Methods of risk assessment and disease classification

ABSTRACT

A method of measuring risk assessment in a patient with appendicitis is disclosed. The method comprises:(a) measuring the TRAIL protein level in a blood sample of the patient;and(b) providing a risk assessment based on the TRAIL protein level.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/336,528 field on Mar. 26, 2019, which is a National Phase of PCTPatent Application No. PCT/IL2017/051089 having International FilingDate of Sep. 27, 2017, which claims the benefit of priority under 35 USC§ 119(e) of U.S. Provisional Patent Application No. 62/401,294 filed onSep. 29, 2016.

The contents of the above applications are all incorporated by referenceas if fully set forth herein in their entirety.

SEQUENCE LISTING STATEMENT

The ASCII file, entitled 92506SequenceListing.txt, created on Jun. 5,2022, comprising 4,425 bytes, submitted concurrently with the filing ofthis application is incorporated herein by reference. The sequencelisting submitted herewith is identical to the sequence listing formingpart of the international application.

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates to methodsof risk assessment in patients for the management of patient healthcare.

Disease assessment is one of the most important tasks in management ofinfectious disease patients. Complement to determining infectionetiology, predicting patient prognosis may affect various aspects ofpatient management including treatment, diagnostic tests (e.g.,microbiology, blood chemistry, radiology etc), and admission. Timelyidentification of patients with higher chance for poor prognosis mayresult in more aggressive patient management procedures including forexample, intensive care unit (ICU) admission, advanced therapeutics,invasive diagnostics or surgical intervention, which could reducecomplications and mortality.

WO 2013/117746 teaches biomarkers including TNF-relatedapoptosis-inducing ligand (TRAIL) for distinguishing between a bacterialand viral infection.

Additional background art includes WO 2016/024278.

SUMMARY OF THE INVENTION

According to an aspect of some embodiments of the present invention,there is provided a method of measuring risk assessment in a patientcomprising:

(a) measuring the TRAIL protein level in a blood sample of the patient;

(b) measuring the level of at least one disease-associated parameter inthe patient; and

(c) providing a risk assessment based on the combination of the TRAILprotein level and the disease-associated parameter level.

According to an aspect of some embodiments of the present invention,there is provided a method of diagnosing an invasive bacterial infectionor a serious bacterial infection (SBI) in a subject comprising measuringthe TRAIL protein level in a blood sample of the subject, wherein whenthe TRAIL protein level is below 25 pg/ml it is indicative of aninvasive bacterial infection or SBI.

According to an aspect of some embodiments of the present invention,there is provided a method of determining a treatment course for asubject presenting with an appendicitis comprising measuring the TRAILprotein level in a blood sample of the subject, wherein when the levelis below a predetermined amount the subject is recommended forappendectomy.

According to some embodiments of the invention, the measuring the levelof at least one disease-associated parameter comprises measuring atleast two components of a clinical index of the patient.

According to some embodiments of the invention, the clinical index isselected from the group consisting of APACHE I, APACHE II, APACHE III,CURB-65, SMART-COP, SAPS II, SAPS III, PIM2, CMM, SOFA, MPM, RIFLE, CP,MODS, LODS, Rochester criteria, Philadelphia Criteria, Milwaukeecriteria and Ranson score.

According to some embodiments of the invention, the disease associatedparameter comprises a disease severity marker.

According to some embodiments of the invention, the disease severitymarker is selected from the group consisting of troponin I, creatin,serum albumin, procalcitonin, interleukin-6, C-reactive protein,Pro-adrenomedullin (ProADM), mid-regional ProADM and prostate specificantigen (PSA).

According to some embodiments of the invention, the disease severitymarker is selected from the group consisting of troponin I,procalcitonin, Pro-adrenomedullin (ProADM), and prostate specificantigen (PSA).

According to some embodiments of the invention, the patient is ahospitalized patient.

According to some embodiments of the invention, the patient is in theEmergency department.

According to some embodiments of the invention, the patient is in theIntensive care unit (ICU).

According to some embodiments of the invention, the risk measurement isused to determine a management course for the patient, the managementcourse being selected from the group consisting of mechanicalventilation, invasive monitoring, sedation, intensive care admission,surgical intervention, drug of last resort and hospital admittance.

According to some embodiments of the invention, the TRAIL protein levelis below 25 pg/ml, the risk assessment is raised.

According to some embodiments of the invention, the level of at leastone disease associated parameter is indicative of a low risk patient andthe TRAIL protein level is below 25 pg/ml, the patient is classified asan intermediate risk patient.

According to some embodiments of the invention, the level of at leastone disease associated parameter is indicative of an intermediate riskpatient and the TRAIL protein level is below 25 pg/ml, the patient isclassified as a high risk patient.

According to some embodiments of the invention, the level of at leastone disease associated parameter is indicative of a high risk patientand the TRAIL protein level is above 25 pg/ml, the patient is classifiedas an intermediate risk patient.

According to some embodiments of the invention, the predetermined amountis 25 pg/ml.

According to some embodiments of the invention, when the level is abovea predetermined amount the subject is recommended for non-surgicaltreatment.

According to some embodiments of the invention, the non-surgicaltreatment comprises antibiotic treatment.

According to some embodiments of the invention, the recommendation isfurther based on at least one measurement selected from the groupconsisting of white blood cell count (WBC) and C-reactive protein (CRP).

According to some embodiments of the invention, the blood sample is afraction of whole blood.

According to some embodiments of the invention, the blood samplecomprises cells selected from the group consisting of lymphocytes,monocytes and granulocytes.

According to some embodiments of the invention, the fraction is serum orplasma.

According to some embodiments of the invention, the measuring isdetermined electrophoretically or immunochemically.

According to some embodiments of the invention, the immunochemicaldetermination is effected by flow cytometry, radioimmunoassay,immunofluorescence, lateral flow immunoassay or by an enzyme-linkedimmunosorbent assay.

According to some embodiments of the invention, the blood sample is afraction of whole blood.

According to some embodiments of the invention, the fraction is serum orplasma.

According to some embodiments of the invention, the blood samplecomprises cells selected from the group consisting of lymphocytes,monocytes and granulocytes.

According to some embodiments of the invention, the invasive bacterialinfection is selected from the group consisting of bacteremia, septicarthritis, abdominal abscess, bacterial meningitis, mastoiditis,nephronia, peritonsillar abscess, deep neck infection, periappendicularabscess, and septic shock.

According to some embodiments of the invention, the SBI is selected fromthe group consisting of bacterial meningitis, bacterial pneumonia,septic arthritis, bacteremia and urinary tract infection (UTI).

According to some embodiments of the invention, the measuring isdetermined electrophoretically or immunochemically.

According to some embodiments of the invention, the immunochemicaldetermination is effected by lateral flow immunoassay, flow cytometry,radioimmunoassay, immunofluorescence or by an enzyme-linkedimmunosorbent assay.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Some embodiments of the invention are herein described, by way ofexample only, with reference to the accompanying drawings. With specificreference now to the drawings in detail, it is stressed that theparticulars shown are by way of example and for purposes of illustrativediscussion of embodiments of the invention. In this regard, thedescription taken with the drawings makes apparent to those skilled inthe art how embodiments of the invention may be practiced.

In the drawings:

FIG. 1: Clinical study workflow.

FIG. 2: Distribution of age of the patients enrolled in the clinicalstudy.

FIG. 3: Distribution of physiological systems of the infectious diseasepatients enrolled in the clinical study.

FIG. 4: Distribution of clinical syndromes of the infectious diseasepatients enrolled in the clinical study.

FIG. 5: Distribution of maximal body temperatures of the infectiousdisease patients enrolled in the clinical study.

FIG. 6: Distribution of time from initiation of symptoms of theinfectious disease patients enrolled in the clinical study.

FIG. 7: Distribution of comorbidities of the patients enrolled in theclinical study.

FIG. 8: Selected pathogens isolated from infectious disease patientsenrolled in the clinical study.

FIG. 9: Distribution of TRAIL serum levels in patients with differentinfection types. Box plots for TRAIL measured over the study cohort arepresented. Line and circle inside the rectangle correspond to groupmedian and average respectively; t-test p-values between bacterial andviral groups and between infectious (bacterial and viral) vs.non-infectious (including healthy subjects) are depicted.

FIG. 10: Different biomarker cutoffs indicative of different clinicalstates. (A) Highly sensitive CRP (HCRP; 0-10 μg/ml) is used for riskstratification of patients with suspicious of myocardial infarction,while higher levels of CRP (>10 μg/ml) are indicative of inflammatorystates, including bacterial and viral infections. (B) Highly sensitiveTRAIL (HTRAIL; 0.5-25 pg/ml) serves as an indicator for diseaseseverity, while higher levels of TRAIL serves as indicators forbacterial infection (25-70 pg/ml), healthy state (70-90 pg/ml), or viralinfections (90-3000 pg/ml).

FIG. 11: Distribution of study patients according to different serumTRAIL levels in the studied cohort.

FIG. 12: Average hospitalization duration (days) in patients withdifferent TRAIL levels.

FIG. 13: Intensive care unit (ICU) admission rates in infectiouspatients with different TRAIL levels.

FIG. 14: Serum TRAIL levels are lower in patients admitted to the ICU

FIG. 15: Patients with TRAIL levels <25 pg/ml (an exemplary cutoff) arestatistically enriched in sub-group of patients with severe clinicalsyndromes. p-values were calculated using the hyper-geometricdistribution. In the entire cohort 93 out of 653 patients (14%) hadTRAIL<25 pg/ml. 7 out of 11 (64%, p<10⁻³) patients with bacteremia hadTRAIL<25 pg/ml, and all 7 patients with septic shock (100%, p<10⁻⁶) hadTRAIL<25 pg/m.

FIGS. 16A-16C: Exemplary algorithm for combining TRAIL/HTRAIL withestablished methods for risk assessment as indicated (A—with initialclinical judgment; B—with a generic severity of disease classificationscore; C—with the APACHE II score). Adding the TRAIL/HTRAIL data canalter the risk level of a patient leading to improved patient managementand health outcome.

FIG. 17: Exemplary algorithm for combining different levels of TRAILwith established methods for risk assessment to alter the risk level ofa patient leading to improved patient management and health outcome.

DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

The present invention, in some embodiments thereof, relates to methodsof risk assessment in patients for the management of patient healthcare.The risk assessment is based on the level of serum protein TNF-relatedapoptosis-inducing ligand (TRAIL) levels.

Disease assessment is one of the most important tasks in management ofinfectious disease patients. As a complement to determining infectionetiology, predicting patient prognosis may affect various aspects ofpatient management including treatment, diagnostic tests (e.g.,microbiology, blood chemistry, radiology etc), and admission. Timelyidentification of patients with higher chance for poor prognosis mayresult in more aggressive patient management procedures including forexample, ICU admission, advanced therapeutics, invasive diagnostics orsurgical intervention, which could reduce complications and mortality.The present inventors previously discovered that TNF-relatedapoptosis-inducing ligand (TRAIL) levels are decreased in bacterialpatients and increased in viral patients compared to non-infectioussubjects (FIG. 9). Based on their findings, they suggested TRAIL as adiagnostic marker for distinguishing between bacterial and viralpatients (e.g. WO 2013/117746). Whilst reducing the present invention topractice, the present inventors have now noted that very low TRAILlevels are correlated with different aspects of disease severity andthus could be used for tailoring the correct patient management course.More specifically, the present inventors have shown that very low TRAILlevels are correlated with higher rates of ICU admission (FIGS. 13 and14) and longer hospital length of stay (FIG. 12). The present inventorspropose that the serum TRAIL level can be used to measure riskassessment in patients so as to ultimately provide a higher healthcarestandard for the patient. The level of TRAIL may be used to assess therisk to the patient of a pre-diagnosed disease. Furthermore, the presentinventors propose that the serum TRAIL level can be used as a prognosticindicator in combination with additional disease severity markers toprovide a more accurate and dependable risk assessment for thepatient—see for example FIGS. 16A-16C.

Thus, according to a first aspect of the present invention there isprovided a method of measuring risk assessment in a patient comprising:

(a) measuring the TRAIL protein level in a blood sample of the patient;

(b) measuring the level of at least one disease-associated parameter inthe patient; and

(c) providing a risk assessment based on the TRAIL protein level anddisease-associated parameter level.

The term “risk assessment” refers to as assignment of a probability toexperience certain adverse events (e.g. death, hospitalization oradmission to ICU) to an individual. Hereby, the individual maypreferably be accounted to a certain risk category, wherein categoriescomprise for instance high risk versus low risk, or risk categoriesbased on numeral values, such as risk category 1, 2, 3, etc.

According to a specific embodiment, the TRAIL protein level is used tostratify the subject into one of four levels—low, intermediate, high andcritical.

In one embodiment, the risk assessment is made in the emergencydepartment of a hospital.

Emergency departments (ED) are progressively overwhelmed by patientswith both urgent and non-urgent problems. This leads to overfilled EDwaiting rooms with long waiting times, detrimental outcomes andunsatisfied patients. As a result, patients needing urgent care may notbe treated in time, whereas patients with non-urgent problems mayunnecessarily receive expensive and dispensable treatments. Time toeffective treatment is among the key predictors for outcomes acrossdifferent medical conditions, including patients with septicaemia,pneumonia, stroke and myocardial infarction. For these reasons, thepresent inventors propose use of the presently disclosed riskstratification system in the ED is essential for an optimal initialtriage of medical patients.

In another embodiment, the risk assessment is made in the intensive careunit of a hospital.

The risk measurement may be used to determine a management course forthe patient. The risk measurement may aid in selection of treatmentpriority and also site-of-care decisions (i.e. outpatient vs. inpatientmanagement) and early identification and organization of post-acute careneeds.

When a patient has been assessed as being at high risk, the managementcourse is typically more aggressive than if he had not been assessed asbeing at high risk. Thus, treatment options such as mechanicalventilation, life support, catheterization, hemofiltration, invasivemonitoring, sedation, intensive care admission, surgical intervention,drug of last resort and hospital admittance may be selected which mayotherwise not have been considered the preferred method of treatment ifthe patient had not been assessed as being at high risk.

Classification of subjects into subgroups as performed in aspects of thepresent invention is preferably done with an acceptable level ofclinical or diagnostic accuracy. An “acceptable degree of diagnosticaccuracy”, is herein defined as a test or assay (such as the test usedin some aspects of the invention) in which the AUC (area under the ROCcurve for the test or assay) is at least 0.60, desirably at least 0.65,more desirably at least 0.70, preferably at least 0.75, more preferablyat least 0.80, and most preferably at least 0.85.

By a “very high degree of diagnostic accuracy”, it is meant a test orassay in which the AUC (area under the ROC curve for the test or assay)is at least 0.75, 0.80, desirably at least 0.85, more desirably at least0.875, preferably at least 0.90, more preferably at least 0.925, andmost preferably at least 0.95.

Alternatively, the methods predict risk with at least 75% totalaccuracy, more preferably 80%, 85%, 90%, 95%, 97%, 98%, 99% or greatertotal accuracy. Alternatively, the methods predict the correctmanagement or treatment with an MCC larger than 0.2, 0.3, 0.4, 0.5, 0.6,0.7, 0.8, 0.9 or 1.0.

A “subject” in the context of the present invention is typically amammal (e.g. human, dog, cat, horse, cow, sheep, pig or goat). Accordingto another embodiment, the subject is a bird (e.g. chicken, turkey, duckor goose). According to a particular embodiment, the subject is a human.The subject may be male or female. The subject may be an adult (e.g.older than 18, 21, or 22 years or a child (e.g. younger than 18, 21 or22 years). In another embodiment, the subject is an adolescent (between12 and 21 years), an infant (29 days to less than 2 years of age) or aneonate (birth through the first 28 days of life).

The subjects of this aspect of the present invention typically presentwith symptoms of a disease—i.e. the subject is a patient.

Exemplary symptoms of a disease include but are not limited to abnormalblood pressure, abnormal heart rate, abnormal red blood count, abnormalwhite blood count, abnormal body temperature, abnormal respiratory rate,abnormal lucidity or alertness.

In one embodiment the symptoms which the subject may present with aresymptoms of an infectious disease. Exemplary symptoms include but arenot limited to fever, nausea, headache, sore throat, runny nose, rashand/or muscle soreness.

In another embodiment the symptoms which the subject may present withare symptoms of a cardiac disease (e.g. chest pain, high bloodpressure).

According to a particular embodiment, the subject does not show signs ofhaving had a heart attack (e.g. has a normal level of creatine kinase,troponin or serum myoglobin, and/or has a normal ECG or EKG).

According to another embodiment, the subject does not have cancer.

In one embodiment, the subject is known not to have sepsis.

In still another embodiment, the symptoms which the subject may presentwith are symptoms of a pulmonary disease (e.g. cough, breathingdifficulty).

In still another embodiment, the symptoms which the subject may presentwith are symptoms of a metabolic disease (e.g. high blood sugar).

It will be appreciated that the subject may have a known pre-diagnoseddisease. Exemplary disease include bacterial infections (e.g.bacteremia, meningitis, respiratory tract infections, urinal tractinfections etc.), viral infections, COPD, chronic lung disease,diabetes, hypertension, sepsis, physical injury and trauma,cardiovascular diseases, multi-organ failure associated diseases,drug-induced nephrotoxicity, acute kidney disease, renal injury, kidneyfailure, advanced cirrhosis and liver failure, acute or chronic leftheart failure, pulmonary hypertension with/without right heart failure,and various types of malignancies.

Sepsis is a life-threatening condition that is caused by inflammatoryresponse to an infection. The early diagnosis of sepsis is essential forclinical intervention before the disease rapidly progresses beyondinitial stages to the more severe stages, such as severe sepsis orseptic shock, which are associated with high mortality.

According to one embodiment, sepsis may be diagnosed as the presence ofSIRS criteria in the presence of a known infection. (SIRS may be definedas 2 or more of the following variables: fever of more than 38° C.(100.4° F.) or less than 36° C. (96.8° F.); heart rate of more than 90beats per minute; respiratory rate of more than 20 breaths per minute orarterial carbon dioxide tension (PaCO2) of less than 32 mm Hg; abnormalwhite blood cell count (>12,000/μL or <4,000/μL or >10% immature [band]forms)).

In another embodiment, sepsis is diagnosed in a subject suspected ofhaving an infection and which fulfils each of the three criteria:

Respiratory rate greater or equal to 22/min;

Altered mentation (e.g. a Glasgow coma score of less than 15);

Systolic blood pressure lower than or equal to 100 mmHg.

Further criteria for diagnosing sepsis are disclosed in Singer et al.2016, 315(8):801-810 JAMA.

Chronic obstructive pulmonary disease (COPD) is an obstructive,inflammatory lung disease characterized by long-term poor airflow. Themain symptoms include shortness of breath and cough with sputumproduction. COPD is a progressive disease, worsening over time.

For any of the aspects disclosed herein, the term “measuring” or“measurement,” or alternatively “detecting” or “detection,” meansassessing the presence, absence, quantity or amount (which can be aneffective amount) of the determinant within a clinical orsubject-derived sample, including the derivation of qualitative orquantitative concentration levels of such determinants.

The phrase “disease associated parameter” includes biomarkers ordeterminants such as polypeptides, polynucleotides and metabolites aswell as clinical determinants.

Examples of clinical determinants include but are not limited to ANC,ALC, Neu (%), Lym (%), Mono (%), Maximal temperature, time fromsymptoms, heart rate, blood pressure, age, Creatinine (Cr), Potassium(K), Pulse and Urea.

Preferably, the disease associated parameter is a biomarker thatcorrelates with risk to the patient (i.e. a disease severity marker).

These include, for example proadrenomedullin (ADM), mid-regionalproadrenomedullin (MR-proADM), a stable peptide of the precursor of ADM,C-reactive protein (CRP) and procalcitonin (PCT) which are used asmarkers of infection/vasodilation; high-sensitivity troponin T assay andnatriuretic peptides which are used as cardiac dysfunction markers;copeptin and cortisol which are used as markers of stress; plasmaneutrophil gelatinase-associated lipocalin, the soluble form ofurokinase-type plasminogen activator and urea which are used as markersof kidney dysfunction; thyroid hormones and proEndothelin-1 which areused as a marker of endothelial activation and lactate which is used asa marker of organ dysfunction. According to a particular embodiment, thedisease severity marker is selected from the group consisting of thelevel of troponin I, procalcitonin, Pro-adrenomedullin (ProADM),Mid-region pro-adrenomedullin (MR-proADM) and prostate specific antigen(PSA).

According to a particular embodiment, the disease associated parameteris Mid-region pro-adrenomedullin (MR-proADM) or Pro-adrenomedullin(ProADM).

Other exemplary blood biomarkers which may be measured according to thisaspect of the present invention include but are not limited to creatin,serum albumin, and interleukin-6.

In a particular embodiment, measuring the level of at least onedisease-associated parameter comprises measuring at least two, at leastthree, at least four, at least five, at least six, at least seven, atleast eight, at least nine or at least nine parameters of a clinicalindex of the subject and providing a risk score based on the clinicalindex.

In one embodiment, measuring the level of at least onedisease-associated parameter comprises measuring all the parameters of aclinical index of the subject.

Exemplary clinical indices include but are not limited to AcutePhysiology and Chronic Health Evaluation (APACHE II) as a measure of howlikely to make it out of intensive care unit; Simplified AcutePhysiology (SAP) score; Glasgow Coma Score (GCS) as an assessment ofconsciousness; Sequential Organ Failure Assessment (SOFA) score as anassessment of person's organ function or rate of failure; ApgarAssessment of a newborn's adjustment to life; Pain perception profile;visual analogue scale (VAS); quality of life metrics such as EDLQ, SF36;depression scale such as CES-D; impact of event scale (IES); orthrombosis risk assessment, or trend therein, or combination of above.

According to a particular embodiment, the clinical index is AcutePhysiology and Chronic Health Evaluation II (APACHE II). This system isan example of a severity of disease classification system that uses apoint score based upon initial values of 12 routine physiologicmeasurements that include: temperature, mean arterial pressure, pHarterial, heart rate, respiratory rate, AaDO2 or PaO2, sodium,potassium, creatinine, hematocrit, white blood cell count, and GlasgowComa Scale. These parameters are measured during the first 24 hoursafter admission, and utilized in additional to information aboutprevious health status (recent surgery, history of severe organinsufficiency, immunocompromised state) and baseline demographics suchas age. An integer score from 0 to 71 is calculated wherein higherscores correspond to more severe disease and a higher risk of death.

Many other predictive models have been developed for various purposeswhich are contemplated by the present invention. Such predictive modelsare used for determining population-based outcome risks. By way ofillustration and not as a limitation, a partial list of predictivemodels comprises SAPS II expanded and predicted mortality, SAPS II andpredicted mortality, APACHE I-IV and predicted mortality, SOFA(Sequential Organ Failure Assessment), MODS (Multiple Organ DysfunctionScore), ODIN (Organ Dysfunctions and/or Infection), MPM (MortalityProbability Model), MPM II LODS (Logistic Organ Dysfunction System),TRIOS (Three days Recalibrated ICU Outcome Score), EUROSCORE (cardiacsurgery), ONTARIO (cardiac surgery), Parsonnet score (cardiac-surgery),System 97 score (cardiac surgery), QMMI score (coronary surgery), Earlymortality risk in redocoronary artery surgery, MPM for cancer patients,POSSUM (Physiologic and Operative Severity Score for the enUmeration ofMortality and Morbidity) (surgery, any), Portsmouth POSSUM (surgery,any), IRISS score: graft failure after lung transplantation, GlasgowComa Score, ISS (Injury Severity Score), RTS (Revised Trauma Score),TRISS (Trauma Injury Severity Score), ASCOT (A Severity CharacterizationOf Trauma), 24 h-ICU Trauma Score, TISS (Therapeutic InterventionScoring System), TISS-28 (simplified TISS), PRISM (Pediatric RISk ofMortality), P-MODS (Pediatric Multiple Organ Dysfunction Score), DORA(Dynamic Objective Risk Assessment), PELOD (Pediatric Logistic OrganDysfunction), PIM II (Paediatric Index of Mortality II), PIM (PaediatricIndex of Mortality), CRIB II (Clinical Risk Index for Babies), CRIB(Clinical Risk Index for Babies), SNAP (Score for Neonatal AcutePhysiology), SNAP-PE (SNAP Perinatal Extension), SNAP II and SNAPPE II,MSSS (Meningococcal Septic Shock Score), GMSPS (Glasgow MeningococcalSepticaemia Prognostic Score), Rotterdam Score (meningococcal septicshock), Children's Coma Score (Raimondi), Paediatric Coma Scale (Simpson& Reilly), and Pediatric Trauma Score, Rochester criteria, PhiladelphiaCriteria, Milwaukee criteria, the last three being specific to neonatalfever/sepsis. Of course, the above list of quality of care metricsdirected to health risk to the patient is not limiting, and othermiscellaneous scores and assessments known in the medical field can beused.

Depending on the nature of the disease associated parameter, themeasurement may be made to the body per se (e.g. blood pressure,temperature) or may be made in a sample retrieved from the patient.

A “sample” in the context of the present invention is a biologicalsample isolated from a subject and can include, by way of example andnot limitation, whole blood, serum, plasma, saliva, mucus, breath,urine, CSF, sputum, sweat, stool, hair, seminal fluid, biopsy,rhinorrhea, tissue biopsy, cytological sample, platelets, reticulocytes,leukocytes, epithelial cells, or whole blood cells.

In a particular embodiment, the sample is a blood sample—e.g. serum,plasma, whole blood. The sample may be a venous sample, peripheral bloodmononuclear cell sample or a peripheral blood sample. Preferably, thesample comprises white blood cells including for example granulocytes,lymphocytes and/or monocytes. In one embodiment, the sample is depletedof red blood cells.

The sample is preferably derived from the subject no more than 72 hours,no more than 60 hours, no more than 48 hours, no more than 36 hours, nomore than one 24 hours or even no more than 12 hours following symptomonset.

The sample may be fresh or frozen.

TRAIL: The protein encoded by this gene is a cytokine that belongs tothe tumor necrosis factor (TNF) ligand family. The present inventioncontemplates measuring either the soluble and/or the membrane form ofthis protein. In one embodiment, only the soluble form of this proteinis measured. Additional names of the gene include without limitationsAPO2L, TNF-related apoptosis-inducing ligand, TNFSF10 and CD253. Thisprotein binds to several members of the TNF receptor superfamily such asTNFRSF10A/TRAILR1, TNFRSF10B/TRAILR2, TNFRSF10C/TRAILR3,TNFRSF10D/TRAILR4, and possibly also to TNFRSF11B/OPG.

Additional information concerning TRAIL is provided in Table 1, hereinbelow.

TABLE 1 Protein Full RefSeq DNA RefSeq symbol Gene Name sequenceproteins TRAIL Tumor necrosis NC_000003.12 NP_001177871.1 factorsuperfamily NC_018914.2 NP_001177872.1 member 10 NT_005612.17NP_003801.1

Exemplary amino acid sequences of TRAIL are set forth in SEQ ID NOs.1-3.

Methods of measuring the level of TRAIL polypeptide are well known inthe art and include, e.g., immunoassays based on antibodies to proteins,aptamers or molecular imprints.

TRAIL can be detected in any suitable manner, but are typically detectedby contacting a sample from the subject with an antibody, which bindsthe TRAIL and then detecting the presence or absence of a reactionproduct. The antibody may be monoclonal, polyclonal, chimeric, or afragment of the foregoing, and the step of detecting the reactionproduct may be carried out with any suitable immunoassay.

In one embodiment, the antibody which specifically binds the determinantis attached (either directly or indirectly) to a signal producing label,including but not limited to a radioactive label, an enzymatic label, ahapten, a reporter dye or a fluorescent label.

Immunoassays carried out in accordance with some embodiments of thepresent invention may be homogeneous assays or heterogeneous assays. Ina homogeneous assay the immunological reaction usually involves thespecific antibody (e.g., anti-determinant antibody), a labeled analyte,and the sample of interest. The signal arising from the label ismodified, directly or indirectly, upon the binding of the antibody tothe labeled analyte. Both the immunological reaction and detection ofthe extent thereof can be carried out in a homogeneous solution.Immunochemical labels, which may be employed, include free radicals,radioisotopes, fluorescent dyes, enzymes, bacteriophages, or coenzymes.

In a heterogeneous assay approach, the reagents are usually the sample,the antibody, and means for producing a detectable signal. Samples asdescribed above may be used. The antibody can be immobilized on asupport, such as a bead (such as protein A and protein G agarose beads),plate or slide, and contacted with the specimen suspected of containingthe antigen in a liquid phase. The support is then separated from theliquid phase and either the support phase or the liquid phase isexamined for a detectable signal employing means for producing suchsignal. The signal is related to the presence of the analyte in thesample. Means for producing a detectable signal include the use ofradioactive labels, fluorescent labels, or enzyme labels. For example,if the antigen to be detected contains a second binding site, anantibody which binds to that site can be conjugated to a detectablegroup and added to the liquid phase reaction solution before theseparation step. The presence of the detectable group on the solidsupport indicates the presence of the antigen in the test sample.Examples of suitable immunoassays are oligonucleotides, immunoblotting,immunofluorescence methods, immunoprecipitation, chemiluminescencemethods, electrochemiluminescence (ECL) or enzyme-linked immunoassays.

Those skilled in the art will be familiar with numerous specificimmunoassay formats and variations thereof which may be useful forcarrying out the method disclosed herein. See generally E. Maggio,Enzyme-Immunoassay, (1980) (CRC Press, Inc., Boca Raton, Fla.); see alsoU.S. Pat. No. 4,727,022 to Skold et al., titled “Methods for ModulatingLigand-Receptor Interactions and their Application,” U.S. Pat. No.4,659,678 to Forrest et al., titled “Immunoassay of Antigens,” U.S. Pat.No. 4,376,110 to David et al., titled “Immunometric Assays UsingMonoclonal Antibodies,” U.S. Pat. No. 4,275,149 to Litman et al., titled“Macromolecular Environment Control in Specific Receptor Assays,” U.S.Pat. No. 4,233,402 to Maggio et al., titled “Reagents and MethodEmploying Channeling,” and U.S. Pat. No. 4,230,767 to Boguslaski et al.,titled “Heterogenous Specific Binding Assay Employing a Coenzyme asLabel.” The determinant can also be detected with antibodies using flowcytometry. Those skilled in the art will be familiar with flowcytometric techniques which may be useful in carrying out the methodsdisclosed herein (Shapiro 2005). These include, without limitation,Cytokine Bead Array (Becton Dickinson) and Luminex technology.

Antibodies can be conjugated to a solid support suitable for adiagnostic assay (e.g., beads such as protein A or protein G agarose,microspheres, plates, slides or wells formed from materials such aslatex or polystyrene) in accordance with known techniques, such aspassive binding. Antibodies as described herein may likewise beconjugated to detectable labels or groups such as radiolabels (e.g.,³⁵S, ¹²⁵I, ¹³¹I), enzyme labels (e.g., horseradish peroxidase, alkalinephosphatase), and fluorescent labels (e.g., fluorescein, Alexa, greenfluorescent protein, rhodamine) in accordance with known techniques.

In particular embodiments, the antibodies of the present invention aremonoclonal antibodies.

Suitable sources for antibodies for the detection of determinantsinclude commercially available sources such as, for example, Abazyme,Abnova, AssayPro, Affinity Biologicals, AntibodyShop, Aviva bioscience,Biogenesis, Biosense Laboratories, Calbiochem, Cell Sciences, ChemiconInternational, Chemokine, Clontech, Cytolab, DAKO, DiagnosticBioSystems, eBioscience, Endocrine Technologies, Enzo Biochem,Eurogentec, Fusion Antibodies, Genesis Biotech, GloboZymes, HaematologicTechnologies, Immunodetect, Immunodiagnostik, Immunometrics, Immunostar,Immunovision, Biogenex, Invitrogen, Jackson ImmunoResearch Laboratory,KMI Diagnostics, Koma Biotech, LabFrontier Life Science Institute, LeeLaboratories, Lifescreen, Maine Biotechnology Services, Mediclone,MicroPharm Ltd., ModiQuest, Molecular Innovations, Molecular Probes,Neoclone, Neuromics, New England Biolabs, Novocastra, Novus Biologicals,Oncogene Research Products, Orbigen, Oxford Biotechnology, Panvera,PerkinElmer Life Sciences, Pharmingen, Phoenix Pharmaceuticals, PierceChemical Company, Polymun Scientific, Polysiences, Inc., PromegaCorporation, Proteogenix, Protos Immunoresearch, QED Biosciences, Inc.,R&D Systems, Repligen, Research Diagnostics, Roboscreen, Santa CruzBiotechnology, Seikagaku America, Serological Corporation, Serotec,SigmaAldrich, StemCell Technologies, Synaptic Systems GmbH, Technopharm,Terra Nova Biotechnology, TiterMax, Trillium Diagnostics, UpstateBiotechnology, US Biological, Vector Laboratories, Wako Pure ChemicalIndustries, and Zeptometrix. However, the skilled artisan can routinelymake antibodies, against any of the polypeptide determinants describedherein.

The presence of a label can be detected by inspection, or a detectorwhich monitors a particular probe or probe combination is used to detectthe detection reagent label. Typical detectors includespectrophotometers, phototubes and photodiodes, microscopes,scintillation counters, cameras, film and the like, as well ascombinations thereof. Those skilled in the art will be familiar withnumerous suitable detectors that widely available from a variety ofcommercial sources and may be useful for carrying out the methoddisclosed herein. Commonly, an optical image of a substrate comprisingbound labeling moieties is digitized for subsequent computer analysis.See generally The Immunoassay Handbook [The Immunoassay Handbook. ThirdEdition. 2005].

Examples of “Monoclonal antibodies for measuring TRAIL”, include withoutlimitation: Mouse, Monoclonal (55B709-3) IgG; Mouse, Monoclonal (2E5)IgG1; Mouse, Monoclonal (2E05) IgG1; Mouse, Monoclonal (M912292) IgG1kappa; Mouse, Monoclonal (IIIF6) IgG2b; Mouse, Monoclonal (2E1-1B9)IgG1; Mouse, Monoclonal (RIK-2) IgG1, kappa; Mouse, Monoclonal M181IgG1; Mouse, Monoclonal VI10E IgG2b; Mouse, Monoclonal MAB375 IgG1;Mouse, Monoclonal MAB687 IgG1; Mouse, Monoclonal HS501 IgG1; Mouse,Monoclonal clone 75411.11 Mouse IgG1; Mouse, Monoclonal T8175-50 IgG;Mouse, Monoclonal 2B2.108 IgG1; Mouse, Monoclonal B-T24 IgG1; Mouse,Monoclonal 55B709.3 IgG1; Mouse, Monoclonal D3 IgG1; Goat, MonoclonalC19 IgG; Rabbit, Monoclonal H257 IgG; Mouse, Monoclonal 500-M49 IgG;Mouse, Monoclonal 05-607 IgG; Mouse, Monoclonal B-T24 IgG1; Rat,Monoclonal (N2B2), IgG2a, kappa; Mouse, Monoclonal (1A7-2B7), IgG1;Mouse, Monoclonal (55B709.3), IgG and Mouse, Monoclonal B-S23*IgG1.

Soluble TRAIL and membrane TRAIL can be distinguished by using differentmeasuring techniques and samples. For example, Soluble TRAL can bemeasured without limitation in cell free samples such as serum orplasma, using without limitation lateral flow immunoassay (LFIA), asfurther described herein below. Membrane TRAIL can be measured insamples that contain cells using cell based assays including withoutlimitation flow cytometry, ELISA, and other immunoassays.

Lateral Flow Immunoassays (LFIA): This is a technology which allowsrapid measurement of analytes at the point of care (POC) and itsunderlying principles are described below. According to one embodiment,LFIA is used in the context of a hand-held device.

The technology is based on a series of capillary beds, such as pieces ofporous paper or sintered polymer. Each of these elements has thecapacity to transport fluid (e.g., urine) spontaneously. The firstelement (the sample pad) acts as a sponge and holds an excess of samplefluid. Once soaked, the fluid migrates to the second element (conjugatepad) in which the manufacturer has stored the so-called conjugate, adried format of bio-active particles (see below) in a salt-sugar matrixthat contains everything to guarantee an optimized chemical reactionbetween the target molecule (e.g., an antigen) and its chemical partner(e.g., antibody) that has been immobilized on the particle's surface.While the sample fluid dissolves the salt-sugar matrix, it alsodissolves the particles and in one combined transport action the sampleand conjugate mix while flowing through the porous structure. In thisway, the analyte binds to the particles while migrating further throughthe third capillary bed. This material has one or more areas (oftencalled stripes) where a third molecule has been immobilized by themanufacturer. By the time the sample-conjugate mix reaches these strips,analyte has been bound on the particle and the third ‘capture’ moleculebinds the complex.

After a while, when more and more fluid has passed the stripes,particles accumulate and the stripe-area changes color. Typically thereare at least two stripes: one (the control) that captures any particleand thereby shows that reaction conditions and technology worked fine,the second contains a specific capture molecule and only captures thoseparticles onto which an analyte molecule has been immobilized. Afterpassing these reaction zones the fluid enters the final porous material,the wick, that simply acts as a waste container. Lateral Flow Tests canoperate as either competitive or sandwich assays.

Different formats may be adopted in LFIA. Strips used for LFIA containfour main components. A brief description of each is given beforedescribing format types.

Sample application pad: It is made of cellulose and/or glass fiber andsample is applied on this pad to start assay. Its function is totransport the sample to other components of lateral flow test strip(LFTS). Sample pad should be capable of transportation of the sample ina smooth, continuous and homogenous manner. Sample application pads aresometimes designed to pretreat the sample before its transportation.This pretreatment may include separation of sample components, removalof interferences, adjustment of pH, etc.

Conjugate pad: It is the place where labeled biorecognition moleculesare dispensed. Material of conjugate pad should immediately releaselabeled conjugate upon contact with moving liquid sample. Labeledconjugate should stay stable over entire life span of lateral flowstrip. Any variations in dispensing, drying or release of conjugate canchange results of assay significantly. Poor preparation of labeledconjugate can adversely affect sensitivity of assay. Glass fiber,cellulose, polyesters and some other materials are used to makeconjugate pad for LFIA. Nature of conjugate pad material has an effecton release of labeled conjugate and sensitivity of assay.

Nitrocellulose membrane: It is highly critical in determiningsensitivity of LFIA. Nitrocellulose membranes are available in differentgrades. Test and control lines are drawn over this piece of membrane. Soan ideal membrane should provide support and good binding to captureprobes (antibodies, aptamers etc.). Nonspecific adsorption over test andcontrol lines may affect results of assay significantly, thus a goodmembrane will be characterized by lesser non-specific adsorption in theregions of test and control lines. Wicking rate of nitrocellulosemembrane can influence assay sensitivity. These membranes are easy touse, inexpensive, and offer high affinity for proteins and otherbiomolecules. Proper dispensing of bioreagents, drying and blocking playa role in improving sensitivity of assay.

Adsorbent pad: It works as sink at the end of the strip. It also helpsin maintaining flow rate of the liquid over the membrane and stops backflow of the sample. Adsorbent capacity to hold liquid can play animportant role in results of assay.

All these components are fixed or mounted over a backing card. Materialsfor backing card are highly flexible because they have nothing to dowith LFIA except providing a platform for proper assembling of all thecomponents. Thus backing card serves as a support and it makes easy tohandle the strip.

Major steps in LFIA are (i) preparation of antibody against targetanalyte (ii) preparation of label (iii) labeling of biorecognitionmolecules (iv) assembling of all components onto a backing card afterdispensing of reagents at their proper pads (v) application of sampleand obtaining results.

Sandwich format: In a typical format, label (Enzymes or nanoparticles orfluorescence dyes) coated antibody or aptamer is immobilized atconjugate pad. This is a temporary adsorption which can be flushed awayby flow of any buffer solution. A primary antibody or aptamer againsttarget analyte is immobilized over test line. A secondary antibody orprobe against labeled conjugate antibody/aptamer is immobilized atcontrol zone.

Sample containing the analyte is applied to the sample application padand it subsequently migrates to the other parts of strip. At conjugatepad, target analyte is captured by the immobilized labeled antibody oraptamer conjugate and results in the formation of labeled antibodyconjugate/analyte complex. This complex now reaches at nitrocellulosemembrane and moves under capillary action. At test line, label antibodyconjugate/analyte complex is captured by another antibody which isprimary to the analyte. Analyte becomes sandwiched between labeled andprimary antibodies forming labeled antibody conjugate/analyte/primaryantibody complex. Excess labeled antibody conjugate will be captured atcontrol zone by secondary antibody. Buffer or excess solution goes toabsorption pad. Intensity of color at test line corresponds to theamount of target analyte and is measured with an optical strip reader orvisually inspected. Appearance of color at control line ensures that astrip is functioning properly.

Competitive format: Such a format suits best for low molecular weightcompounds which cannot bind two antibodies simultaneously. Absence ofcolor at test line is an indication for the presence of analyte whileappearance of color both at test and control lines indicates a negativeresult. Competitive format has two layouts. In the first layout,solution containing target analyte is applied onto the sampleapplication pad and prefixed labeled biomolecule (antibody/aptamer)conjugate gets hydrated and starts flowing with moving liquid. Test linecontains pre-immobilized antigen (same analyte to be detected) whichbinds specifically to label conjugate. Control line containspre-immobilized secondary antibody which has the ability to bind withlabeled antibody conjugate. When liquid sample reaches at the test line,pre-immobilized antigen will bind to the labeled conjugate in casetarget analyte in sample solution is absent or present in such a lowquantity that some sites of labeled antibody conjugate were vacant.Antigen in the sample solution and the one which is immobilized at testline of strip compete to bind with labeled conjugate. In another layout,labeled analyte conjugate is dispensed at conjugate pad while a primaryantibody to analyte is dispensed at test line. After application ofanalyte solution a competition takes place between analyte and labeledanalyte to bind with primary antibody at test line.

Multiplex detection format: Multiplex detection format is used fordetection of more than one target species and assay is performed overthe strip containing test lines equal to number of target species to beanalyzed. It is highly desirable to analyze multiple analytessimultaneously under same set of conditions. Multiplex detection formatis very useful in clinical diagnosis where multiple analytes which areinter-dependent in deciding about the stage of a disease are to bedetected. Lateral flow strips for this purpose can be built in variousways i.e. by increasing length and test lines on conventional strip,making other structures like stars or T-shapes. Shape of strip for LFIAwill be dictated by number of target analytes. Miniaturized versions ofLFIA based on microarrays for multiplex detection of DNA sequences havebeen reported to have several advantages such as less consumption oftest reagents, requirement of lesser sample volume and bettersensitivity.

Labels: Any material that is used as a label should be detectable atvery low concentrations and it should retain its properties uponconjugation with biorecognition molecules. This conjugation is alsoexpected not to change features of biorecognition probes. Ease inconjugation with biomolecules and stability over longer period of timeare desirable features for a good label. Concentrations of labels downto 10⁻⁹ M are optically detectable. After the completion of assay, somelabels generate direct signal (as color from gold colloidal) whileothers require additional steps to produce analytical signal (as enzymesproduce detectable product upon reaction with suitable substrate). Hencethe labels which give direct signal are preferable in LFA because ofless time consumption and reduced procedure.

Gold nanoparticles: Colloidal gold nanoparticles are the most commonlyused labels in LFA. Colloidal gold is inert and gives very perfectspherical particles. These particles have very high affinity towardbiomolecules and can be easily functionalized. Optical properties ofgold nanoparticles are dependent on size and shape. Size of particlescan be tuned by use of suitable chemical additives. Their uniquefeatures include environment friendly preparation, high affinity towardproteins and biomolecules, enhanced stability, exceptionally highervalues for charge transfer and good optical signaling. Optical signal ofgold nanoparticles in colorimetric LFA can be amplified by deposition ofsilver, gold nanoparticles and enzymes.

Magnetic particles and aggregates: Colored magnetic particles producecolor at the test line which is measured by an optical strip reader butmagnetic signals coming from magnetic particles can also be used asdetection signals and recorded by a magnetic assay reader. Magneticsignals are stable for longer time compared to optical signals and theyenhance sensitivity of LFA by 10 to 1000 folds.

Fluorescent and luminescent materials: Fluorescent molecules are widelyused in LFA as labels and the amount of fluorescence is used toquantitate the concentration of analyte in the sample. Detection ofproteins is accomplished by using organic fluorophores such as rhodamineas labels in LFA.

Current developments in nanomaterial have headed to manufacture ofquantum dots which display very unique electrical and opticalproperties. These semiconducting particles are not only water solublebut can also be easily combined with biomolecules because of closenessin dimensions. Owing to their unique optical properties, quantum dotshave come up as a substitute to organic fluorescent dyes Like goldnanoparticles QDs show size dependent optical properties and a broadspectrum of wavelengths can be monitored. Single light source issufficient to excite quantum dots of all different sizes. QDs have highphoto stability and absorption coefficients.

Upconverting phosphors (UCP) are characterized by their excitation ininfra-red region and emission in high energy visible region. Compared toother fluorescent materials, they have a unique advantage of not showingany auto fluorescence. Because of their excitation in IR regions, theydo not photo degrade biomolecules. A major advantage lies in theirproduction from easily available bulk materials. Although difference inbatch to batch preparation of UCP reporters can affect sensitivity ofanalysis in LFA, it was observed that they can enhance sensitivity ofanalytical signal by 10 to 100 folds compared to gold nanoparticles orcolored latex beads, when analysis is carried out under same set ofbiological conditions.

Enzymes: Enzymes are also employed as labels in LFA. But they increaseone step in LFA which is application of suitable substrate aftercomplete assay. This substrate will produce color at test and controllines as a result of enzymatic reaction. In case of enzymes, selectionof suitable enzyme substrate combination is one necessary requirement inorder to get a colored product for strip reader or electroactive productfor electrochemical detection. In other words, sensitivity of detectionis dependent on enzyme substrate combination.

Colloidal carbon: Colloidal carbon is comparatively inexpensive labeland its production can be easily scaled up. Because of their blackcolor, carbon NPs can be easily detected with high sensitivity.Colloidal carbon can be functionalized with a large variety ofbiomolecules for detection of low and high molecular weight analytes.

Detection systems: In case of gold nanoparticles or other colorproducing labels, qualitative or semi-quantitative analysis can be doneby visual inspection of colors at test and control lines. The majoradvantage of visual inspection is rapid qualitative answer in “Yes” or“NO”. Such quick replies about presence of an analyte in clinicalanalysis have very high importance. Such tests help doctors to make animmediate decision near the patients in hospitals in situations wheretest results from central labs cannot be waited for because of huge timeconsumption. But for quantification, optical strip readers are employedfor measurement of the intensity of colors produced at test and controllines of strip. This is achieved by inserting the strips into a stripreader and intensities are recorded simultaneously by imaging softwares.Optical images of the strips can also be recorded with a camera and thenprocessed by using a suitable software. Procedure includes properplacement of strip under the camera and a controlled amount of light isthrown on the areas to be observed. Such systems use monochromatic lightand wavelength of light can be adjusted to get a good contrast amongtest and control lines and background. In order to provide goodquantitative and reproducible results, detection system should besensitive to different intensities of colors. Optical standards can beused to calibrate an optical reader device. Automated systems haveadvantages over manual imaging and processing in terms of timeconsumption, interpretation of results and adjustment of variables.

In case of fluorescent labels, a fluorescence strip reader is used torecord fluorescence intensity of test and control lines. Fluorescencebrightness of test line increased with an increase in nitratedceruloplasmin concentration in human serum when it was detected with afluorescence strip reader. A photoelectric sensor was also used fordetection in LFIA where colloidal gold is exposed to light emittingdiode and resulting photoelectrons are recorded. Chemiluminescence whichresults from reaction of enzyme and substrate is measured as a responseto amount of target analyte. Magnetic strip readers and electrochemicaldetectors are also reported as detection systems in LFTS but they arenot very common. Selection of detector is mainly determined by the labelemployed in analysis.

As mentioned, the levels of TRAIL and the disease-associated parameterare combined to provide a combined score for risk analysis.

In one embodiment, when the TRAIL protein level is below a predeterminedamount, the risk assessment based on the disease-associated parameter israised. The predetermined level of serum TRAIL protein may be below 30pg/ml, below 25 pg/ml, below 20 pg/ml, below 15 pg/ml or even below 10pg/ml.

Exemplary ranges for indicating a high risk patient include but are notlimited to 0.5-30 pg/ml, 0.5-25 pg/ml, 0.5-20 pg/ml, 0.5-15 pg/ml,0.5-10 pg/ml, 0.5-5 pg/ml, 1-10 pg/ml; 10-20 pg/ml; 5-10 pg/ml; 5-25pg/ml; 0.5-20 pg/ml; 0.5-5 pg/ml; 0.5-26 pg/ml; 0.5-27 pg/ml; 0.5-28pg/ml; 0.5-29 pg/ml; 0.5-30 pg/ml; 0.5-35 pg/ml.

For example, when the level of at least one disease severity marker isindicative of a low risk patient and the TRAIL protein level is below 30pg/ml, below 25 pg/ml, below 20 pg/ml, below 15 pg/ml or even below 10pg/ml, the patient may be classified as an intermediate risk patient.

When the level of at least one disease severity marker is indicative ofan intermediate risk patient and the TRAIL protein level is below 30pg/ml, below 25 pg/ml, below 20 pg/ml, below 15 pg/ml or even below 10pg/ml, the patient may be classified as a high risk patient.

When the level of at least one disease severity marker is indicative ofa high risk patient and the TRAIL protein level is above 25 pg/ml, thepatient may be classified as an intermediate risk patient.

For example, a patient can be considered severely ill if the APACHE IIscore surpasses a certain threshold and if TRAIL is below a certainthreshold. In another example a patient with an APACHE II score of 0-9will be considered as low risk if its TRAIL levels are above 25 pg/ml,but as intermediate risk if a serum TRAIL level below 25 pg/ml wasdetected—see for example FIG. 16C.

Below are examples of how TRAIL levels may affect the risk assessmentbased on individual disease severity parameters.

MR-proADM: When used alone, levels below <0.75 nmol/L indicate low risk(e.g. outpatient care may be recommended) to patients with lowerrespiratory tract infections, levels between 0.75 nmol/L and 1.5 nmol/Lindicate intermediate risk (e.g. short-term hospitalization may berecommended) and levels above 1.5 nmol/L indicate high risk (e.g. ICUadmission may be recommended). If TRAIL levels are below 25 pg/ml, thelow risk group may now be considered an intermediate or high risk groupand the intermediate risk group may be considered a high risk group.

Procalcitonin: When used alone, levels below 0.5 ng/mL indicate low riskfor progression to severe sepsis and/or septic shock (e.g. outpatientcare may be recommended), levels between 0.5-2 ng/ml indicateintermediate risk (e.g. short-term hospitalization may be recommended)and levels above 2.0 ng/ml indicate high risk (e.g. ICU admission may berecommended). If TRAIL levels are below 25 pg/ml, the low risk group maynow be considered an intermediate or high risk group and theintermediate risk group may be considered a high risk group.

Prostate specific antigen: When used alone, levels below 10 ng/mLindicate low risk (15% chance of biochemical recurrence within 5years)—, levels between 10-20 ng/ml indicate intermediate risk (e.g. 40%chance of biochemical recurrence within 5 years), and levels above 20ng/ml indicate high risk (e.g. 40% chance of biochemical recurrencewithin 5 years). If TRAIL levels are below 25 pg/ml, the low risk groupmay now be considered an intermediate or high risk group and theintermediate risk group may be considered a high risk group.

Troponin I: When used alone, levels below 0.4 ng/mL indicate low risk ofmortality, levels between 0.4-5 ng/ml indicate intermediate risk ofmortality and levels above 5.0 ng/ml indicate high risk of mortality. IfTRAIL levels are below 25 pg/ml, the low risk group may now beconsidered an intermediate or high risk group and the intermediate riskgroup may be considered a high risk group. If TRAIL levels are below 25pg/ml, the low risk group may now be considered an intermediate or highrisk group and the intermediate risk group may be considered a high riskgroup.

Particular combinations of TRAIL and at least one disease associatedparameter are provided herein below:

TRAIL+Mid-region pro-adrenomedullin (MR-proADM)

TRAIL+CRP+MR-proADM TRAIL+PCT+MR-proADM TRAIL+IL-6+MR-proADMTRAIL+NGAL+MR-proADM TRAIL+CRP+IP-10+MR-proADM TRAIL+CRP+IL-6+MR-proADMTRAIL+PCT+IL-6+MR-proADM TRAIL+PCT+IP-10+MR-proADMTRAIL+PCT+NGAL+MR-proADM TRAIL+CRP+IL-6+PCT+MR-proADMTRAIL+CRP+IL-6+NGAL+MR-proADM TRAIL+CRP+IL-6+IP-10+MR-proADMTRAIL+NGAL+IL-6+PCT+MR-proADM TRAIL+IP-10+IL-6+PCT+MR-proADMTRAIL+WBC+MR-proADM TRAIL+ANC+MR-proADM TRAIL+WBC TRAIL+ANCTRAIL+temperature

TRAIL+mean arterial pressureTRAIL+pH arterialTRAIL+heart rateTRAIL+respiratory rate

TRAIL+AaDO2 or PaO2 TRAIL+sodium TRAIL+potassium TRAIL+creatinineTRAIL+hematocrit TRAIL+Glasgow Coma Scale

It will be appreciated that additional markers may also be used whenperforming the risk analysis according to this aspect of the presentinvention. The additional markers may aid in increasing the accuracy ofthe risk analysis.

Exemplary additional markers include for example those disclosed inTable 2 herein below.

TABLE 2 Protein Full RefSeq DNA RefSeq symbol Gene Name sequenceproteins CRP C-reactive protein, NC_000001.11 NP_000558.2pentraxin-related NT_004487.20 NC_018912.2 IP-10 Chemokine (C-X-CNC_000004.12 NP_001556.2 motif) ligand 10 NC_018915.2 NT_016354.20IL1R/IL1R1/IL1RA Interleukin 1 NC_000002.12 NP_000868.1 receptor, type INT_005403.18 NP_001275635.1 NC_018913.2 SAA/SAA1 Serum amyloid A1NC_000011.10 NP_000322.2 NC_018922.2 NP_001171477.1 NT_009237.19NP_954630.1 TREM1 Triggering receptor NC_000006.12 NP_001229518.1expressed on myeloid NT_007592.16 NP_001229519.1 cells 1 NC_018917.2NP_061113.1 TREM2 Triggering receptor NC_000006.12 NP_001258750.1expressed on myeloid NT_007592.16 NP_061838.1 cells 2 NC_018917.2 RSAD2Radical S-adenosyl NC_000002.12 NP_542388.2 methionine domainNT_005334.17 containing 2 NC_018913.2 NGAL Lipocalin 2 NC_000009.12NP_005555.2 NC_018920.2 NT_008470.20 MMP8 Matrix NC_000011.10NP_001291370.1 metallopeptidase 8 NT_033899.9 NP_001291371.1 NC_018922.2NP_002415.1 Procalcitonin Calcitonin-related NC_000011.10 NP_001029124.1(PCT) polypeptide alpha NC_018922.2 NP_001029125.1 NT_009237.19NP_001732.1 IL-6 Interleukin 6 NC_000007.14 NP_000591.1 NT_007819.18NC_018918.2 MX1 MX Dynamin-Like NC_000021.9 NP_001138397.1 GTPase 1NT_011512.12 NP_001171517.1 NC_018932.2 NP_001269849.1 NP_002453.2 ADMAdrenomedullin NC_000011.10 NP_001115.1 NC_018922.2 ENSP00000431438NT_009237.19 ENSP00000433062 ENSP00000434354 ENSP00000434749ENSP00000435124 ENSP00000436607 ENSP00000436837 ENSP00000278175Neopterin 2-amino-6-(1,2,3- N/A N/A trihydroxypropyl)- 1H-pteridin-4-oneIUPAC name

Combining the levels of TRAIL and the at least one disease severityparameter (and any other contemplated marker or determinant) istypically effected using algorithms or formulas as described hereinbelow.

A “formula,” “algorithm,” or “model” is any mathematical equation,algorithmic, analytical or programmed process, or statistical techniquethat takes one or more continuous or categorical inputs (herein called“parameters”) and calculates an output value, sometimes referred to asan “index” or “index value”. Non-limiting examples of “formulas” includesums, ratios, and regression operators, such as coefficients orexponents, biomarker value transformations and normalizations(including, without limitation, those normalization schemes based onclinical-determinants, such as gender, age, or ethnicity), rules andguidelines, statistical classification models, and neural networkstrained on historical populations. Of particular use in combiningdeterminants are linear and non-linear equations and statisticalclassification analyses to determine the relationship between levels ofdeterminants detected in a subject sample and the subject's riskassessment. In panel and combination construction, of particularinterest are structural and syntactic statistical classificationalgorithms, and methods of index construction, utilizing patternrecognition features, including established techniques such ascross-correlation, Principal Components Analysis (PCA), factor rotation,Logistic Regression (LogReg), Linear Discriminant Analysis (LDA),Eigengene Linear Discriminant Analysis (ELDA), Support Vector Machines(SVM), Random Forest (RF), Recursive Partitioning Tree (RPART), as wellas other related decision tree classification techniques, ShrunkenCentroids (SC), StepAIC, Kth-Nearest Neighbor, Boosting, Decision Trees,Neural Networks, Bayesian Networks, and Hidden Markov Models, amongothers. Other techniques may be used in survival and time to eventhazard analysis, including Cox, Weibull, Kaplan-Meier and Greenwoodmodels well known to those of skill in the art. Many of these techniquesare useful either combined with a determinant selection technique, suchas forward selection, backwards selection, or stepwise selection,complete enumeration of all potential panels of a given size, geneticalgorithms, or they may themselves include biomarker selectionmethodologies in their own technique. These may be coupled withinformation criteria, such as Akaike's Information Criterion (AIC) orBayes Information Criterion (BIC), in order to quantify the tradeoffbetween additional biomarkers and model improvement, and to aid inminimizing overfit. The resulting predictive models may be validated inother studies, or cross-validated in the study they were originallytrained in, using such techniques as Bootstrap, Leave-One-Out (LOO) and10-Fold cross-validation (10-Fold CV).

Any formula may be used to combine TRAIL the at least one diseaseseverity parameter results into indices useful in the practice of theinvention. As indicated above, and without limitation, such indices mayindicate, among the various other indications, the probability,likelihood, absolute or relative risk, time to or rate of conversionfrom one to another disease states, or make predictions of futurebiomarker measurements of the disease. This may be for a specific timeperiod or horizon, or for remaining lifetime risk, or simply be providedas an index relative to another reference subject population.

Although various preferred formula are described here, several othermodel and formula types beyond those mentioned herein and in thedefinitions above are well known to one skilled in the art. The actualmodel type or formula used may itself be selected from the field ofpotential models based on the performance and diagnostic accuracycharacteristics of its results in a training population.

Exemplary formulas include the broad class of statistical classificationalgorithms, and in particular the use of discriminant analysis. The goalof discriminant analysis is to predict class membership from apreviously identified set of features. In the case of lineardiscriminant analysis (LDA), the linear combination of features isidentified that maximizes the separation among groups by some criteria.Features can be identified for LDA using an eigengene based approachwith different thresholds (ELDA) or a stepping algorithm based on amultivariate analysis of variance (MANOVA). Forward, backward, andstepwise algorithms can be performed that minimize the probability of noseparation based on the Hotelling-Lawley statistic.

Eigengene-based Linear Discriminant Analysis (ELDA) is a featureselection technique developed by Shen et al. (2006). The formula selectsfeatures (e.g. biomarkers) in a multivariate framework using a modifiedeigen analysis to identify features associated with the most importanteigenvectors. “Important” is defined as those eigenvectors that explainthe most variance in the differences among samples that are trying to beclassified relative to some threshold.

A support vector machine (SVM) is a classification formula that attemptsto find a hyperplane that separates two classes. This hyperplanecontains support vectors, data points that are exactly the margindistance away from the hyperplane. In the likely event that noseparating hyperplane exists in the current dimensions of the data, thedimensionality is expanded greatly by projecting the data into largerdimensions by taking non-linear functions of the original variables(Venables and Ripley, 2002). Although not required, filtering offeatures for SVM often improves prediction. Features (e.g., biomarkers)can be identified for a support vector machine using a non-parametricKruskal-Wallis (KW) test to select the best univariate features. Arandom forest (RF, Breiman, 2001) or recursive partitioning (RPART,Breiman et al., 1984) can also be used separately or in combination toidentify biomarker combinations that are most important. Both KW and RFrequire that a number of features be selected from the total. RPARTcreates a single classification tree using a subset of availablebiomarkers.

Other formula may be used in order to pre-process the results ofindividual determinant measurement into more valuable forms ofinformation, prior to their presentation to the predictive formula. Mostnotably, normalization of biomarker results, using either commonmathematical transformations such as logarithmic or logistic functions,as normal or other distribution positions, in reference to apopulation's mean values, etc. are all well known to those skilled inthe art. Of particular interest are a set of normalizations based onclinical-determinants such as age, time from symptoms, gender, race, orsex, where specific formula are used solely on subjects within a classor continuously combining a clinical-determinants as an input. In othercases, analyte-based biomarkers can be combined into calculatedvariables which are subsequently presented to a formula.

In addition to the individual parameter values of one subjectpotentially being normalized, an overall predictive formula for allsubjects, or any known class of subjects, may itself be recalibrated orotherwise adjusted based on adjustment for a population's expectedprevalence and mean biomarker parameter values, according to thetechnique outlined in D'Agostino et al, (2001) JAMA 286:180-187, orother similar normalization and recalibration techniques. Suchepidemiological adjustment statistics may be captured, confirmed,improved and updated continuously through a registry of past datapresented to the model, which may be machine readable or otherwise, oroccasionally through the retrospective query of stored samples orreference to historical studies of such parameters and statistics.Additional examples that may be the subject of formula recalibration orother adjustments include statistics used in studies by Pepe, M. S. etal, 2004 on the limitations of odds ratios; Cook, N. R., 2007 relatingto ROC curves. Finally, the numeric result of a classifier formulaitself may be transformed post-processing by its reference to an actualclinical population and study results and observed endpoints, in orderto calibrate to absolute risk and provide confidence intervals forvarying numeric results of the classifier or risk formula.

Some determinants may exhibit trends that depends on the patient age(e.g. the population baseline may rise or fall as a function of age).One can use an ‘Age dependent normalization or stratification’ scheme toadjust for age related differences. Performing age dependentnormalization or stratification can be used to improve the accuracy ofdeterminants for differentiating between different types of infections.For example, one skilled in the art can generate a function that fitsthe population mean levels of each determinant as function of age anduse it to normalize the determinant of individual subjects levels acrossdifferent ages. Another example is to stratify subjects according totheir age and determine age specific thresholds or index values for eachage group independently.

As mentioned the level of TRAIL can be used to make a risk assessment asto a patient and further to decide on the appropriate treatment course.

Thus, according to another aspect of the present invention there isprovided a method of determining a treatment course for a subjectpresenting with an appendicitis comprising measuring the TRAIL proteinlevel in a blood sample of the subject, wherein when the level is belowa predetermined amount the subject is recommended for appendectomy.

Typically the subject presenting with the appendicitis exhibits at leastone, two, three, four or all of the following symptoms: elevated CRPlevels, PCT levels, findings on ultrasound or CT scan, nausea andvomiting, epigastric pain migrating to the right lower quadrant (RLQ),tenderness in RLQ, rebound pain, elevated temperature, shift of WBCs tothe left, anorexia or leukocytosis.

Measuring the TRAIL protein level has been described herein above.

According to this aspect of the present invention, the predeterminedamount below which the subject is recommended for appendectomy is below30 pg/ml, below 25 pg/ml, below 20 pg/ml, below 15 pg/ml or even below10 pg/ml. Exemplary ranges for appendectomy treatment include but arenot limited to 0.5-30 pg/ml, 0.5-25 pg/ml, 0.5-20 pg/ml, 0.5-15 pg/ml,0.5-10 pg/ml, 0.5-5 pg/ml.

Conversely, when the TRAIL level is above this predetermined amount, thesubject may be recommended non-surgical treatments—e.g. antibiotictreatment. In one embodiment, the when the level is between 30-70 pg/ml,the subject is recommended a non-surgical treatment, when the level isbetween 25-70 pg/ml, the subject is recommended a non-surgicaltreatment, when the level is between 30-80 pg/ml, the subject isrecommended a non-surgical treatment, when the level is between 25-80pg/ml, the subject is recommended a non-surgical treatment, when thelevel is between 20-70 pg/ml, the subject is recommended a non-surgicaltreatment, when the level is between 20-80 pg/ml, the subject isrecommended a non-surgical treatment.

In one embodiment, the TRAIL levels are used to improve the accuracy ofvarious scoring systems aimed to identify acute appendicitis or tostratify acute appendicitis patients according to disease severity inorder to recommend appendectomy or antibiotic treatment. An example ofsuch scoring system is the MANTRELS score.

As well as using the TRAIL protein serum levels, the present inventorscontemplate use of additional factors and measurements to help decide atreatment course for the subject with appendicitis. Such factorsinclude, but are not limited to white blood cell count (WBC) andC-reactive protein (CRP) blood level. Additional markers that may beused for determining treatment for appendicitis are any of thosedescribed herein (see for example Table 2).

The present inventors have further shown that patients with TRAIL levelsbelow 25 pg/ml were more likely to have serious bacterial infections,(e.g. invasive bacterial infections) or other severe clinical syndromes,for example bacteremia and septic shock, as these syndromes werestatistically enriched in the low TRAIL sub-group (64% (7/11) of allbacteremia cases P<10⁻³, and 100% (7/7) of all septic shock cases,P<10⁻⁶; FIG. 15.

Thus, according to yet another aspect of the present invention there isprovided a method of diagnosing a serious bacterial infection in asubject comprising measuring the TRAIL protein level in a blood sampleof the subject, wherein when the TRAIL protein level is below 25 pg/mlit is indicative of a serious bacterial infection.

The method according to this aspect of the present invention may be usedto “rule in” a serious bacterial infection. Alternatively, the methodmay be used to rule out a non-serious bacterial infection. The methodaccording to some embodiments can be used to “rule in” a seriousbacterial infection and “rule out” a non-bacterial disease.

Serious bacterial infections may include for example the followingclinical syndromes: meningitis, sepsis, pneumonia, septic arthritis andcellulitis, bacteremia, urinary tract infection (UTI), andPyelonephritis.

According to a particular embodiment, the serious bacterial infection isnot sepsis.

Thus, according to yet another aspect of the present invention there isprovided a method of diagnosing an invasive bacterial infection in asubject comprising measuring the TRAIL protein level in a blood sampleof the subject, wherein when the TRAIL protein level is below 25 pg/mlit is indicative of an invasive bacterial infection.

The method according to this aspect of the present invention may be usedto “rule in” an invasive bacterial infection. Alternatively, the methodmay be used to rule out a non-invasive bacterial infection. The methodaccording to some embodiments can be used to “rule in” an invasivebacterial infection and “rule out” a non-bacterial disease.

Invasive bacterial infections occur when the bacteria get past thedefenses of the person who is infected. This may occur when a person hassores or other breaks in the skin that allow the bacteria to get intothe tissue, or when the person's ability to fight off the infection isdecreased because of chronic illness or an illness that affects theimmune system.

Although healthy people can get invasive bacterial disease, people withchronic illnesses like cancer, diabetes, and chronic heart or lungdisease, and those who use medications such as steroids have a higherrisk. Persons with skin lesions (such as cuts, chicken pox, surgicalwounds), the elderly, and adults with a history of alcohol abuse orinjection drug use also have a higher risk for disease.

Exemplary invasive bacterial diseases include but are not limited toMeningococcal Disease, Invasive; Staphylococcus Aureus Infections; Drugresistant (MRSA, VISA, VRSA) Streptococcal Disease, Group A Invasive orStreptococcal TSS; Streptococcal Disease, Invasive Group B.

Other contemplated invasive bacterial diseases include bacteremia,septic arthritis, abdominal abscess, bacterial meningitis, mastoiditis,nephronia, peritonsillar abscess, deep neck infection, periappendicularabscess and septic shock.

According to a particular embodiment, the invasive bacterial disease isnot septic shock.

It will be appreciated that as well as measuring TRAIL, the presentinventors contemplate use of additional markers that may aid in thediagnosis of invasive bacterial disease. These include any of themarkers taught in the present application such as procalcitonin,lactate, lactic acid, CRP, WBC, ANC, or pathogen related determinants(such as nucleic acids) of one of the following pathogens:Staphylococcus Aureus; Drug resistant Staphylococcus Aureus (MRSA, VISA,VRSA), Group A or Group B Streptococci.

Measuring serum protein TRAIL levels is described herein above.

In one embodiment, when the TRAIL protein level is below a predeterminedamount, the chance that the subject is suffering from an invasivebacterial infection or from a serious bacterial infection is increased.The predetermined level of serum TRAIL protein may be below 30 pg/ml,below 25 pg/ml, below 20 pg/ml, below 15 pg/ml or even below 10 pg/ml.

Exemplary ranges for indicating a high risk of invasive bacterialinfection include but are not limited to 0.5-30 pg/ml, 0.5-25 pg/ml,0.5-20 pg/ml, 0.5-15 pg/ml, 0.5-10 pg/ml, 0.5-5 pg/ml, 1-10 pg/ml; 10-20pg/ml; 5-10 pg/ml; 5-25 pg/ml; 0.5-20 pg/ml; 0.5-5 pg/ml; 0.5-26 pg/ml;0.5-27 pg/ml; 0.5-28 pg/ml; 0.5-29 pg/ml; 0.5-30 pg/ml; 0.5-35 pg/ml.

In the context of the present invention, the following abbreviations maybe used: ANC=Absolute neutrophil count; ANN=Artificial neural networks;AUC=Area under the receiver operating curve; BP=Bordetella pertussis;CHF=Congestive heart failure; CI=Confidence interval; CID=Congenitalimmune deficiency; CLL=Chronic lymphocytic leukemia;CMV=Cytomegalovirus; CNS=Central nervous system; COPD=Chronicobstructive pulmonary disease; CP=Chlamydophila pneumonia;CRP=C-reactive protein; CSF=Cerebrospinal fluid; CV=Coefficient ofvariation; DOR=Diagnostic odds ratio; EBV=Epstein bar virus;eCRF=Electronic case report form; ED=Emergency department,ELISA=Enzyme-linked immunosorbent assay; FDR=False discovery rate;FMF=Familial Mediterranean fever; G-CSF=Granulocyte colony-stimulatingfactor; GM-CSF=Granulocyte-macrophage colony-stimulating factor;HBV=Hepatitis B virus; HCV=Hepatitis C virus; HI=Haemophilus influenza;HIV=Human immunodeficiency virus; IDE=Infectious disease experts;IL=Interleukin; IRB=institutional review board; IVIG=Intravenousimmunoglobulin; KNN=K-nearest neighbors; LP=Legionella pneumophila;LR+=Positive likelihood ratio; LR−=Negative likelihood ratio; LRTI=Lowerrespiratory tract infections; mAb=Monoclonal antibodies; MDD=Minimumdetectable dose; MDS=Myelodysplastic syndrome; MP=Mycoplasma pneumonia;MPD=Myeloproliferative disease; NPV=Negative predictive value;PCT=Procalcitonin; PED=Pediatric emergency department; PPV=Positivepredictive value; QA=Quality assurance; RSV=Respiratory syncytial virus;RV=Rhinovirus; SIRS=systemic inflammatory syndrome; SP=Streptococcuspneumonia; STARD=Standards for Reporting of Diagnostic Accuracy;SVM=Support vector machine; TNF=Tumor necrosis factor; URTI=Upperrespiratory tract infection; UTI=Urinary tract infection; WBC=Whiteblood cell; WS=Wilcoxon rank-sum.

In the context of the present invention, the following statistical termsmay be used:

“TP” is true positive, means positive test result that accuratelyreflects the tested-for activity. For example in the context of thepresent invention a TP, is for example but not limited to, trulyclassifying a bacterial infection as such.

“TN” is true negative, means negative test result that accuratelyreflects the tested-for activity. For example in the context of thepresent invention a TN, is for example but not limited to, trulyclassifying a viral infection as such.

“FN” is false negative, means a result that appears negative but failsto reveal a situation. For example in the context of the presentinvention a FN, is for example but not limited to, falsely classifying abacterial infection as a viral infection.

“FP” is false positive, means test result that is erroneously classifiedin a positive category. For example in the context of the presentinvention a FP, is for example but not limited to, falsely classifying aviral infection as a bacterial infection.

“Sensitivity” is calculated by TP/(TP+FN) or the true positive fractionof disease subjects.

“Specificity” is calculated by TN/(TN+FP) or the true negative fractionof non-disease or normal subjects.

“Total accuracy” is calculated by (TN+TP)/(TN+FP+TP+FN).

“Positive predictive value” or “PPV” is calculated by TP/(TP+FP) or thetrue positive fraction of all positive test results. It is inherentlyimpacted by the prevalence of the disease and pre-test probability ofthe population intended to be tested.

“Negative predictive value” or “NPV” is calculated by TN/(TN+FN) or thetrue negative fraction of all negative test results. It also isinherently impacted by the prevalence of the disease and pre-testprobability of the population intended to be tested. See, e.g.,O'Marcaigh A S, Jacobson R M, “Estimating The Predictive Value Of ADiagnostic Test, How To Prevent Misleading Or Confusing Results,” Clin.Ped. 1993, 32(8): 485-491, which discusses specificity, sensitivity, andpositive and negative predictive values of a test, e.g., a clinicaldiagnostic test.

“MCC” (Mathews Correlation coefficient) is calculated as follows:MCC=(TP*TN −FP*FN)/{(TP+FN)*(TP+FP)*(TN+FP)*(TN+FN)}{circumflex over( )}0.5 where TP, FP, TN, FN are true-positives, false-positives,true-negatives, and false-negatives, respectively. Note that MCC valuesrange between −1 to +1, indicating completely wrong and perfectclassification, respectively. An MCC of 0 indicates randomclassification. MCC has been shown to be a useful for combiningsensitivity and specificity into a single metric (Baldi, Brunak et al.2000). It is also useful for measuring and optimizing classificationaccuracy in cases of unbalanced class sizes (Baldi, Brunak et al. 2000).

“Accuracy” refers to the degree of conformity of a measured orcalculated quantity (a test reported value) to its actual (or true)value. Clinical accuracy relates to the proportion of true outcomes(true positives (TP) or true negatives (TN) versus misclassifiedoutcomes (false positives (FP) or false negatives (FN)), and may bestated as a sensitivity, specificity, positive predictive values (PPV)or negative predictive values (NPV), Mathews correlation coefficient(MCC), or as a likelihood, odds ratio, Receiver Operating Characteristic(ROC) curve, Area Under the Curve (AUC) among other measures.

“Analytical accuracy” refers to the reproducibility and predictabilityof the measurement process itself, and may be summarized in suchmeasurements as coefficients of variation (CV), Pearson correlation, andtests of concordance and calibration of the same samples or controlswith different times, users, equipment and/or reagents. These and otherconsiderations in evaluating new biomarkers are also summarized inVasan, 2006.

“Performance” is a term that relates to the overall usefulness andquality of a diagnostic or prognostic test, including, among others,clinical and analytical accuracy, other analytical and processcharacteristics, such as use characteristics (e.g., stability, ease ofuse), health economic value, and relative costs of components of thetest. Any of these factors may be the source of superior performance andthus usefulness of the test, and may be measured by appropriate“performance metrics,” such as AUC and MCC, time to result, shelf life,etc. as relevant.

By “statistically significant”, it is meant that the alteration isgreater than what might be expected to happen by chance alone (whichcould be a “false positive”). Statistical significance can be determinedby any method known in the art. Commonly used measures of significanceinclude the p-value, which presents the probability of obtaining aresult at least as extreme as a given data point, assuming the datapoint was the result of chance alone. A result is often consideredhighly significant at a p-value of 0.05 or less.

The term “determinant” as used herein refers to a disease associatedparameter or biomarker.

As used herein the term “about” refers to ±10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to”.

The term “consisting of” means “including and limited to”.

The term “consisting essentially of” means that the composition, methodor structure may include additional ingredients, steps and/or parts, butonly if the additional ingredients, steps and/or parts do not materiallyalter the basic and novel characteristics of the claimed composition,method or structure.

Throughout this application, various embodiments of this invention maybe presented in a range format. It should be understood that thedescription in range format is merely for convenience and brevity andshould not be construed as an inflexible limitation on the scope of theinvention. Accordingly, the description of a range should be consideredto have specifically disclosed all the possible subranges as well asindividual numerical values within that range. For example, descriptionof a range such as from 1 to 6 should be considered to have specificallydisclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numberswithin that range, for example, 1, 2, 3, 4, 5, and 6. This appliesregardless of the breadth of the range.

As used herein the term “method” refers to manners, means, techniquesand procedures for accomplishing a given task including, but not limitedto, those manners, means, techniques and procedures either known to, orreadily developed from known manners, means, techniques and proceduresby practitioners of the chemical, pharmacological, biological,biochemical and medical arts.

As used herein, the term “treating” includes abrogating, substantiallyinhibiting, slowing or reversing the progression of a condition,substantially ameliorating clinical or aesthetical symptoms of acondition or substantially preventing the appearance of clinical oraesthetical symptoms of a condition.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable subcombination or as suitable in any other describedembodiment of the invention. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

Various embodiments and aspects of the present invention as delineatedhereinabove and as claimed in the claims section below find experimentalsupport in the following examples.

EXAMPLES

Reference is now made to the following examples, which together with theabove descriptions illustrate some embodiments of the invention in a nonlimiting fashion.

Generally, the nomenclature used herein and the laboratory proceduresutilized in the present invention include molecular, biochemical,microbiological and recombinant DNA techniques. Such techniques arethoroughly explained in the literature. See, for example, “MolecularCloning: A laboratory Manual” Sambrook et al., (1989); “CurrentProtocols in Molecular Biology” Volumes I-III Ausubel, R. M., ed.(1994); Ausubel et al., “Current Protocols in Molecular Biology”, JohnWiley and Sons, Baltimore, Md. (1989); Perbal, “A Practical Guide toMolecular Cloning”, John Wiley & Sons, New York (1988); Watson et al.,“Recombinant DNA”, Scientific American Books, New York; Birren et al.(eds) “Genome Analysis: A Laboratory Manual Series”, Vols. 1-4, ColdSpring Harbor Laboratory Press, New York (1998); methodologies as setforth in U.S. Pat. Nos. 4,666,828; 4,683,202; 4,801,531; 5,192,659 and5,272,057; “Cell Biology: A Laboratory Handbook”, Volumes I-III Cellis,J. E., ed. (1994); “Culture of Animal Cells—A Manual of Basic Technique”by Freshney, Wiley-Liss, N. Y. (1994), Third Edition; “Current Protocolsin Immunology” Volumes I-III Coligan J. E., ed. (1994); Stites et al.(eds), “Basic and Clinical Immunology” (8th Edition), Appleton & Lange,Norwalk, Conn. (1994); Mishell and Shiigi (eds), “Selected Methods inCellular Immunology”, W. H. Freeman and Co., New York (1980); availableimmunoassays are extensively described in the patent and scientificliterature, see, for example, U.S. Pat. Nos. 3,791,932; 3,839,153;3,850,752; 3,850,578; 3,853,987; 3,867,517; 3,879,262; 3,901,654;3,935,074; 3,984,533; 3,996,345; 4,034,074; 4,098,876; 4,879,219;5,011,771 and 5,281,521; “Oligonucleotide Synthesis” Gait, M. J., ed.(1984); “Nucleic Acid Hybridization” Hames, B. D., and Higgins S. J.,eds. (1985); “Transcription and Translation” Hames, B. D., and HigginsS. J., eds. (1984); “Animal Cell Culture” Freshney, R. I., ed. (1986);“Immobilized Cells and Enzymes” IRL Press, (1986); “A Practical Guide toMolecular Cloning” Perbal, B., (1984) and “Methods in Enzymology” Vol.1-317, Academic Press; “PCR Protocols: A Guide To Methods AndApplications”, Academic Press, San Diego, Calif. (1990); Marshak et al.,“Strategies for Protein Purification and Characterization—A LaboratoryCourse Manual” CSHL Press (1996); all of which are incorporated byreference as if fully set forth herein. Other general references areprovided throughout this document. The procedures therein are believedto be well known in the art and are provided for the convenience of thereader. All the information contained therein is incorporated herein byreference.

Example 1

Methods

Study population: 1002 patients with suspected acute infectious diseaseand non-infectious controls were prospectively recruited fromHillel-Yaffe and Bnai-Zion Medical Centers, Israel (NCT01917461). Thestudy was conducted according to the guidelines and recommendations ofGood Clinical Practice and the Declaration of Helsinki. Written informedconsent was obtained from each participant or legal guardian, asapplicable.

Pediatric patients (<18 years) were recruited from pediatric emergencydepartments (PED), pediatric wards and surgical departments, and adults(>18 years) from emergency departments (ED), internal medicinedepartments and surgical departments. Informed consent was obtained fromeach participant or legal guardian, as applicable. Inclusion criteriafor the infectious disease cohort included: clinical suspicion of anacute infectious disease, peak fever >37.5° C. since symptoms onset, andduration of symptoms <12 days. Inclusion criteria for the control groupincluded: clinical impression of a non-infectious disease (e.g. trauma,stroke and myocardial infarction), or healthy subjects. Exclusioncriteria included: evidence of any episode of acute infectious diseasein the two weeks preceding enrollment; diagnosed congenital immunedeficiency; current treatment with immunosuppressive or immunomodulatorytherapy; active malignancy, proven or suspected human immunodeficiencyvirus (HIV)-1, hepatitis B virus (HBV), or hepatitis C virus (HCV)infection. Importantly, in order to enable broad generalization,antibiotic treatment at enrollment did not cause exclusion from thestudy.

Enrollment process and data collection: For each patient, the followingbaseline variables were recorded: demographics, physical examination,medical history (e.g. main complaints, underlying diseases,chronically-administered medications, comorbidities, time of symptomonset, and peak temperature), complete blood count (CBC) obtained atenrollment, and chemistry panel (e.g. creatinine, urea, electrolytes,and liver enzymes). A nasal swab was obtained from each patient forfurther microbiological investigation, and a blood sample was obtainedfor protein screening and validation. Additional samples were obtainedas deemed appropriate by the physician (e.g. urine and stool samples incases of suspected urinary tract infection [UTI], and gastroenteritis[GI] respectively). Radiological tests were obtained at the discretionof the physician (e.g. chest X-ray for suspected lower respiratory tractinfection [LRTI]). Thirty days after enrollment, disease course andresponse to treatment were recorded. All information was recorded in acustom electronic case report form (eCRF).

Microbiological investigation: Patients underwent two multiplex-PCRdiagnostic assays from nasal swab samples: (i) Seeplex™ RV15 (n=713),for detection of parainfluenza virus 1, 2, 3, and 4, coronavirus229E/NL63, adenovirus A/B/C/D/E, bocavirus 1/2/3/4, influenza virus Aand B, metapneumovirus, coronavirus OC43, rhinovirus A/B/C, respiratorysyncytial virus A and B, and Enterovirus, and (ii) Seeplex™ PB6 (n=633)for detection of Streptococcus pneumoniae, Haemophilus influenzae,Chlamydophila pneumoniae, Legionella pneumophila, Bordetella pertussis,and Mycoplasma pneumoniae. Multiplex-PCR assays were performed by acertified service laboratory. Patients were also tested for additionalpathogens according to their suspected clinical syndrome, including:blood culture (n=420), urine culture (n=188) and stool culture forShigella spp., Campylobacter spp. and Salmonella spp. (n=66);serological testing (IgM and/or IgG) for cytomegalovirus (CMV),Epstein-Barr virus (EBV), Mycoplasma Pneumonia, and Coxiella burnetii(Q-Fever) (n=167, n=130, n=206 and n=41 respectively).

Establishing the reference standard: A rigorous composite referencestandard was created following recommendations of the Standards forReporting of Diagnostic Accuracy (STARD; FIG. 1).¹ First, a thoroughclinical and microbiological investigation was performed for eachpatient as described above. Then, all the data collected throughout thedisease course was reviewed by a panel of three physicians. For adultpatients (>18 years) the panel included the attending physician and twoinfectious disease specialists, while for children and adolescents (<18years) it included the attending pediatrician, an infectious diseaseexpert and a senior attending pediatrician. Each panel member assignedone of the following diagnostic labels to each patient: (i) bacterial;(ii) viral; (iii) no apparent infectious disease or healthy (controls);and (iv) mixed infections (bacteria plus virus). Importantly, the panelmembers were blinded to the labeling of their peers and to the resultsof the signature.

Patient prognostic measures: Various clinical measures were used toretrospectively asses patient's prognosis such as ICU admission, needfor mechanical ventilation or surgical interventions, hospital length ofstay, patient re-admission to the hospital, and the manifestation of asevere clinical syndrome like bacteremia or septic shock.

Samples, procedures and protein measurements: Venous blood samples werestored at 4° C. for up to 5 hours on site and subsequently fractionatedinto plasma, serum and total leukocytes and stored at −80° C. Nasalswabs and stool samples were stored at 4° C. for up to 72 hours andsubsequently transported to a certified service laboratory for multiplexPCR-based assay. TRAIL was measured using commercial ELISA kits (MeMedDiagnostics).

Statistical analysis: The primary analysis was based on area under thereceiver operating characteristics curve (AUC), Sensitivity (TP/P),Specificity (TN/N), Positive predictive value (PPV=TP/[TP+FP]), Negativepredictive value (NPV=TN/[TN+FN]), where P, N, TP and TN correspond topositives (bacterial patients), negatives (viral patients), truepositives (correctly diagnosed bacterial patients), and true negatives(correctly diagnosed viral patients), respectively. Statistical analysiswas performed with MATLAB.

Results

Patient characteristics: Three physicians independently assigned a labelto each patient (either bacterial, viral, controls, or indeterminate).98 patients were labeled as indeterminate, because the physicians couldnot establish disease etiology or there was no majority labeling. Adetailed characterization of the analyzed cohort is depicted in FIGS.2-8. Briefly, the cohort was balanced with respect to gender (47%females, 53% males) and included 56% pediatric patients (<18 years) and44% adults (>18 years). Patients presented with a wide range of clinicalsyndromes (e.g. RTI, UTI, and systemic infections), maximal temperatures(36-41.5° C.), and time from symptoms onset (0-12 days). Altogether, 56pathogen species were detected that are responsible for the vastmajority of acute infectious diseases in the Western world.

TRAIL as a Marker for Predicting Disease Severity and Risk Assessment:

In the studied cohort, 667 patients had TRAIL levels higher than 25pg/ml and 98 patients had TRAIL levels lower than 25 pg/ml (FIG. 11),out of which 89 had a bacterial etiology, 4 viral etiology and 5 withnon-infectious condition. The 98 patients with TRAIL levels lower than25 pg/ml had poorer patient prognosis and outcome, and higher diseaseseverity compared to patients with higher TRAIL levels. For example,their hospitalization duration was close to 4-fold longer compared topatients with higher TRAIL levels (7.5±1.17 vs. 1.9±0.1, days,average±standard error, P<10⁻⁵; FIG. 12). All patients from theinfectious disease group that required mechanical ventilation and ICUadmission had TRAIL levels lower than 25 pg/ml (6/93 TRAIL<25 pg/ml vs.0/560 TRAIL>25 pg/ml, P<10⁻⁵; FIG. 13). Median serum concentrations were9 pg/ml vs. 80 pg respectively, (ranksum P<0.001, FIG. 14), for severelyill and all other patients respectively. Strikingly, the lowest TRAILlevels (<5 pg/ml) were measured in the only two children that died inthe entire cohort. Finally, patients with TRAIL levels <25 pg/ml weremore likely to have invasive bacterial infections or other severeclinical syndromes, for example bacteremia and septic shock, as thesesyndromes were statistically enriched in the low TRAIL sub-group (64%(7/11) of all bacteremia cases P<10⁻³, and 100% (7/7) of all septicshock cases, P<10⁻⁶; (FIG. 15).

Example 2

Appendicitis is defined as an inflammation of the inner lining of thevermiform appendix that spreads to its other parts. Despite diagnosticand therapeutic advancement in medicine, appendicitis remains a clinicalemergency and is one of the more common causes of acute abdominal pain.Laboratory tests such as CBC, CRP, liver, pancreatic function tests andurine analysis do not have findings specific for appendicitis, but theymay be helpful to confirm diagnosis in patients with an atypicalpresentation. Appendectomy remains the standard treatment ofappendicitis, however, in the last few years a number of studiesregarding an alternative, antibiotic approach, have been conducted.Preliminary evidence suggests that non-operative management in selectedlow risk patients with acute appendicitis exhibited higher quality oflife scores and is associated with lower appendicitis-related healthcare costs [Minneci P C, et al J Am Coll Surg 2014; 219:272; Svensson JF, et al. Ann Surg 2015; 261:67; Minneci PC, et al. JAMA Surg 2016;151:408; Telem D A. JAMA 2016; 315:811; Tanaka Y, et al. J Pediatr Surg2015; 50:1893]. Furthermore, early detection and treatment of patientswho are at high risk of appendicitis complications, such as perforationand peritonitis, is imperative and should promote early appendectomy[Bickell N A, J Am Coll Surg 2006; 202:401; Nomura 0, et al. PediatrEmerg Care 2012; 28:792].

Thus new diagnostic and prognostic markers are needed to successfullydifferentiate patients who will benefit an operative management fromthose who will be better treated with a more conservative approach. Thepresent inventors therefore sought to evaluate the ability of TRAIL topredict outcome and recommend proper management course in acuteappendicitis patients.

Methods

Presented herein, are two case studies of acute appendicitis patientswith different disease course for whom blood TRAIL levels were measured.Venous blood samples were stored at 4° C. for up to 5 hours on site andsubsequently fractionated into plasma, serum and total leukocytes andstored at −80° C. TRAIL was measured from serum fraction usingcommercial ELISA kits (MeMed Diagnostics).

Results

Case Number 10542

A 13 year old male presented to the emergency department with a two dayhistory of fever, abdominal pain and vomiting. On physical examination,RLQ tenderness with positive rebound and Mcburney signs were noted.

Main laboratory results: CRP 396.5 mg/1, WBC 17,090 cells/μl

Ultrasound test revealed an inflamed appendix, 10 mm in diameter andextensive gutters fluid collection. An early appendectomy operation wasconducted in which a perforated appendix was noticed and resected. Onthe 6^(th) post-operative day surgical wound infection was noted withpurulent discharge, on ultrasound exam 6 cm pelvic fluid collection.Compatible with wound culture results, patient received I.V Ceftriaxoneand Metronidazole. Patient was discharged after a total hospitalizationduration of 21 days.

Measured TRAIL levels: 15.4 pg/ml.

Case Number: 10565

A three-year-old boy presented to the emergency department with a fourday history of fever up to 41.4° C. (106.5° F.), chills and emesis a dayprior to presentation. On physical examination, the patient appearedsick, showed right lower quadrant (RLQ) tenderness and had a positiverebound sign without peritonitis. Main laboratory results: CRP 242.2mg/1, WBC 13,000 cells/W. On ultrasound test, the appendix could not bevisualized. The patient was scheduled for an early appendectomyoperation, however, due to parents' objection to an operation and a CTscan, conservative antibiotic treatment with intravenous (I.V)Ceftriaxone was initiated. A second ultrasound test, a day followingantibiotic treatment administration, revealed normal appendix withoutsigns of inflammation. Patient was discharged without surgicalprocedure.

Measured TRAIL levels: 80.9 pg/ml.

In case #10565, TRAIL levels were in the normal range (FIG. 10) andcorrectly predicted a positive outcome using a conservative antibiotictreatment. Low TRAIL levels were a successful indicator of a severedisease state of a perforated appendix in case #10542. These two casesdemonstrate the ability of TRAIL to differentiate between mild andsevere cases of suspected appendicitis and to recommend eitherconservative drug treatment vs invasive operative treatment according toTRAIL levels.

It is the intent of the Applicant(s) that all publications, patents andpatent applications referred to in this specification are to beincorporated in their entirety by reference into the specification, asif each individual publication, patent or patent application wasspecifically and individually noted when referenced that it is to beincorporated herein by reference. In addition, citation oridentification of any reference in this application shall not beconstrued as an admission that such reference is available as prior artto the present invention. To the extent that section headings are used,they should not be construed as necessarily limiting. In addition, anypriority document(s) of this application is/are hereby incorporatedherein by reference in its/their entirety.

REFERENCES

-   1. Bossuyt, P. M. et al. The STARD Statement for Reporting Studies    of Diagnostic Accuracy: Explanation and Elaboration. Ann Intern Med    138, W1-W12 (2003).-   2. Niemz, A., Ferguson, T. M. & Boyle, D. S. Point-of-care nucleic    acid testing for infectious diseases. Trends Biotechnol. 29, 240-250    (2011).-   3. Craw, P. & Balachandran, W. Isothermal nucleic acid amplification    technologies for point-of-care diagnostics: a critical review. Lab    Chip 12, 2469-2486 (2012).-   4. Kim, K. H., Shin, J. H. & Kim, S. Y. The Clinical Significance of    Nasopharyngeal Carriages in Immunocompromised Children as Assessed.    The Korean Journal of Hematology 44, 220 (2009).-   5. Shin, J. H., Han, H. Y. & Kim, S. Y. Detection of nasopharyngeal    carriages in children by multiplex reverse transcriptase-polymerase    chain reaction. Korean Journal of Pediatrics 52, 1358 (2009).-   6. Jung, C. L., Lee, M. A. & Chung, W. S. Clinical Evaluation of the    Multiplex PCR Assay for the Detection of Bacterial Pathogens in    Respiratory Specimens from Patients with Pneumonia. Korean Journal    of Clinical Microbiology 13, 40 (2010).-   7. Rhedin, S. et al. Clinical Utility of PCR for Common Viruses in    Acute Respiratory Illness. Pediatrics peds.2013-3042 (2014).    doi:10.1542/peds.2013-3042-   8. Bogaert, D., De Groot, R. & Hermans, P. W. M. Streptococcus    pneumoniae colonisation: the key to pneumococcal disease. Lancet    Infect Dis 4, 144-154 (2004).-   9. Spuesens, E. B. M. et al. Carriage of Mycoplasma pneumoniae in    the Upper Respiratory Tract of Symptomatic and Asymptomatic    Children: An Observational Study. PLoS Med 10, e1001444 (2013).

What is claimed is:
 1. A method of treating a subject comprising: (a)measuring the TRAIL protein level in a blood sample of the subject; (b)measuring the level of at least two components of a clinical index ofthe subject; (c) providing a risk assessment based on the combination ofsaid TRAIL protein level and said level of said at least two componentsof said clinical index; and (d) treating the subject according to therisk assessment.
 2. The method of claim 1, wherein said measuring thelevel of said at least two components of said clinical index comprisesmeasuring all the components of said clinical index.
 3. The method ofclaim 2, wherein said clinical index is selected from the groupconsisting of APACHE I, APACHE II, APACHE III, CURB-65, SMART-COP, SAPSII, SAPS III, PIM2, CMM, SOFA, MPM, RIFLE, CP, MODS, LODS, Rochestercriteria, Philadelphia Criteria, Milwaukee criteria and Ranson score. 4.The method of claim 1, wherein the subject is a hospitalized subject. 5.The method of claim 1, wherein the subject is in the Emergencydepartment.
 6. The method claim 1, wherein the subject is in theIntensive care unit (ICU).
 7. The method of claim 1, wherein when theTRAIL protein level is below 25 pg/ml, the risk assessment is raised. 8.The method of claim 1, wherein when said level of said at least twocomponents of said clinical index is indicative of a low risk patientand said TRAIL protein level is below 25 pg/ml, the patient isclassified as an intermediate risk patient.
 9. The method of claim 1,wherein said level of said at least two components of said clinicalindex is indicative of an intermediate risk patient and said TRAILprotein level is below 25 pg/ml, the patient is classified as a highrisk patient.
 10. The method of claim 9, wherein said treating comprisesa management course selected from the group consisting of mechanicalventilation, invasive monitoring, sedation, intensive care admission,surgical intervention, drug of last resort and hospital admittance. 11.The method of claim 1, wherein when said level of said at least twocomponents of said clinical index is indicative of a high risk patientand said TRAIL protein level is above 25 pg/ml, the patient isclassified as an intermediate risk patient.
 12. The method of claim 1,wherein said blood sample is a fraction of whole blood.
 13. The methodof claim 1, wherein said blood sample comprises cells selected from thegroup consisting of lymphocytes, monocytes and granulocytes.
 14. Themethod of claim 1, wherein said fraction is serum or plasma.
 15. Themethod of claim 1, wherein said measuring is determinedelectrophoretically or immunochemically.
 16. The method of claim 15,wherein said immunochemical determination is effected by flow cytometry,radioimmunoassay, immunofluorescence, lateral flow immunoassay or by anenzyme-linked immunosorbent assay.